The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
In noise detection and analysis systems, acoustic transducers such as microphones are employed to collect noise signals emanating from one or more noise sources. However, single, omni-directional microphone measurements are incapable of discriminating between different noise signals emanating from multiple, and typically spatially separated and/or distributed, noise sources. The presence of multiple noise sources severely complicates the analysis of correlation data from the microphones.
An example of a difficult noise correlation problem is the noise radiated simultaneously from the inlet and exhaust nozzles of a jet aircraft engine, that is, two spatially separated noise sources. The inlet/exhaust noise sources separately radiate outwards to the external measurement field. If the inlet noise and the exhaust noise contain a noise signal emanating from a common source, for example a particular component or surface within the jet engine, then they can have a measurable degree of correlation in the external measurement field. The first challenge is thus determining whether or not the inlet and exhaust noise sources are correlated. This is complicated by noise from other various components of the engine that emanate from the engine or the downstream exhaust flow and are picked up by the microphones, as well as extraneous noise sources (e.g., vehicles operating in the area; aircraft flying overhead; construction work) existing in the measurement environment that is picked up by the microphones. These forms of extraneous noise, both coming from within and external to the engine and from sources remote from the engine, are picked up by the microphones and operate to “mask” the existence of any noise signal having a correlation that is picked up by the microphones.
In the above described example, even if a correlation between two noise signals, picked up by two spatially separated microphones, is determined to exist, then the next challenge is to determine the locations in the external measurement field at which the correlation values are a maximum (or of meaningful high level). Still another challenge is the determination of the spatial extent (in the measurement field) of the correlation which arises from spatially distributed noise sources. An example of such spatially distributed noise sources might be correlated noise sources along a wing flap trailing edge; correlated noise sources within the jet mixing region downstream of the jet engine exhaust nozzle; etc.
From the foregoing, it will be appreciated that determining when a correlation exists between two spatially separated noise sources presents significant challenges. Determining the locations within the measurement field where the correlations are a maximum, as well as the spatial extent within the measurement field where the maximum correlation exists, represent even further significant challenges with presently available noise monitoring/measuring systems and methods.